Installation and setup

A Python distribution of version 3.7 or higher is required to run this project. Before you begin using make commands for data pulling or ETL steps it is important to make sure your configs.yaml file is properly configured for your needs.

Setting up configuration files

Before using the make commands related to data pulling and ETL, make sure the configs.yaml file is properly configured for your needs. Additionally, to perform data pulling, you should create àn twitter-creds.yaml file (e.g., touch twitter-creds.yaml ) and should be configured as follows:

    account_type: <ACC_TYPE>
    consumer_key: <CONSUMER_KEY>
    consumer_secret: <CONSUMER_SECRET>

    account_type: <ACC_TYPE>
    consumer_key: <CONSUMER_KEY>
    consumer_secret: <CONSUMER_SECRET>

Please note that if you do not intend to do any kind of data pull tests you may disregard the first key. In the event you do want to do some sort of testing for data pulling, you must edit the make data_pull command in the Makefile script accordingly.


The src package requires the dependencies listed in the requirements.txt file:

pip install -r requirements.txt

If you intend to compile the documentation locally, you must also install the dependencies listed in the file:

pip install -r

The project’s environment and requirements can also be installed using make commands (See section Commands ).


All make scripts/commands can be configured through the configs.yaml file. The following set of commands should allow you to setup the project with minimal effort:

# Clone the project.
git clone
cd solve-iwmi

# Create and activate an environment
make create_environment

# Adapt this line below if you're not running conda
conda activate solve-iwmi

# Install project requirements
make requirements

# Read the corresponding subchapter to pull data from Twitter
make data_pull

# Set up Elastic Search database (it might take a while to initialize...)
make database

# Extract, Transform and Load data (the last step can be to save data as JSON files instead)
make etl

# Load preprocessed data into ES
make load_es

#Update the data in es and create networks index for ES
make update_es

# Close the database
make close_database

Alternatively, if you only intend to use the API, you can just install the src package using pip and GitHub:

pip install -U git+


Once all data is created you can then bring up the website. In the web folder make sure that you add an env file

Env file should be called .env and look like

REACT_APP_API_URL=(website ip or dns)

Once the env is setup all you have to do if the database is setup correctly just bring the dockers up with the command

docker-compose up

Frontend port is set to 3000 and backend to 8080